Antenna Season Report Notebook¶

Josh Dillon, Last Revised January 2022

This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.

In [1]:
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
In [2]:
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
In [3]:
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "65"
csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
In [4]:
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))

Antenna 65 Report

In [5]:
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
In [6]:
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 32 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_
Found 32 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
In [7]:
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'

Load relevant info from summary CSVs¶

In [8]:
this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
            antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
        else:
            antnum = int(row['Ant'])
        if antnum != int(antenna):
            continue
        
        if np.issubdtype(type(row['Node']), np.integer):
            row['Node'] = str(row['Node'])
        if type(row['Node']) == str and row['Node'].isnumeric():
            row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break
In [9]:
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])

Table 1: Per-Night RTP Summary Info For This Atenna¶

This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.

In [10]:
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))

Antenna 65, Node N03:

Out[10]:
JDs A Priori Status Auto Metrics Flags Dead Fraction in Ant Metrics (Jee) Dead Fraction in Ant Metrics (Jnn) Crossed Fraction in Ant Metrics Flag Fraction Before Redcal Flagged By Redcal chi^2 Fraction ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score Average Dead Ant Metric (Jee) Average Dead Ant Metric (Jnn) Average Crossed Ant Metric Median chi^2 Per Antenna (Jee) Median chi^2 Per Antenna (Jnn)
2460015 digital_ok 100.00% 100.00% 100.00% 0.00% - - 26.059449 24.690559 14.135122 14.128389 5.900273 7.044868 5.863791 7.153203 0.0226 0.0247 0.0024 nan nan
2460014 digital_ok 100.00% 100.00% 100.00% 0.00% - - 24.593088 21.670589 10.887531 10.805839 9.014692 10.569293 4.372422 5.625308 0.0226 0.0243 0.0019 nan nan
2460013 digital_ok 100.00% 100.00% 100.00% 0.00% - - 26.074163 24.898225 14.245945 14.136088 6.117275 7.190007 6.894251 8.651129 0.0225 0.0244 0.0022 nan nan
2460012 digital_ok 100.00% 100.00% 100.00% 0.00% - - 24.667275 23.563509 13.984136 13.894777 6.576353 7.801293 7.681827 9.770243 0.0227 0.0284 0.0057 nan nan
2460011 digital_ok 100.00% 100.00% 100.00% 0.00% - - 26.543196 24.725632 18.658014 18.613437 13.740578 16.210966 6.037885 7.499853 0.0228 0.0286 0.0063 nan nan
2460010 digital_ok 100.00% 100.00% 100.00% 0.00% - - 28.705253 27.072601 15.052712 15.379989 9.265841 10.470842 5.662304 7.158898 0.0228 0.0294 0.0068 nan nan
2460009 digital_ok 100.00% 100.00% 100.00% 0.00% - - 27.384916 25.660041 16.658361 16.868447 7.435949 8.905910 5.243936 7.105534 0.0227 0.0280 0.0056 nan nan
2460008 digital_ok 100.00% 100.00% 100.00% 0.00% - - 31.661936 30.211714 18.280907 18.579914 6.695802 7.806454 5.487439 6.744117 0.0229 0.0306 0.0080 nan nan
2460007 digital_ok 100.00% 100.00% 100.00% 0.00% - - 23.637347 22.587889 14.271669 14.513646 6.012330 7.262833 5.908707 7.513667 0.0227 0.0281 0.0057 nan nan
2459999 digital_ok 0.00% 100.00% 99.92% 0.00% - - nan nan nan nan nan nan nan nan 0.1117 0.1738 0.1310 nan nan
2459998 digital_ok 100.00% 100.00% 100.00% 0.00% - - 21.093794 19.987338 12.268315 12.368718 8.156339 10.400137 4.689562 6.376948 0.0513 0.0261 0.0196 nan nan
2459997 digital_ok 100.00% 100.00% 100.00% 0.00% - - 23.267372 22.017959 13.019299 13.266608 7.824141 9.683493 8.295054 10.287782 0.0531 0.0285 0.0195 nan nan
2459996 digital_ok 100.00% 100.00% 100.00% 0.00% - - 25.573229 23.819132 16.151280 16.153198 7.408880 9.306543 3.396996 4.547491 0.0442 0.0270 0.0101 nan nan
2459995 digital_ok 0.00% 0.00% 0.00% 0.00% - - 0.512253 1.558083 0.894202 1.249383 -0.368593 1.223226 3.848835 2.134812 0.5901 0.6082 0.4003 nan nan
2459994 digital_ok 0.00% 0.00% 0.00% 0.00% - - 0.682575 1.607135 0.683002 1.307043 -0.235262 0.865021 -0.378571 -0.456227 0.5875 0.6036 0.3957 nan nan
2459993 digital_ok 0.00% 0.00% 0.00% 0.00% - - 0.135874 1.115308 0.425464 1.129750 -0.422386 0.374328 2.058626 0.465625 0.5653 0.6081 0.4135 nan nan
2459991 digital_ok 0.00% 0.00% 0.00% 0.00% - - 0.571673 1.769952 0.562291 1.185523 -0.413544 0.614940 0.402824 -0.001076 0.5998 0.6117 0.4033 nan nan
2459990 digital_ok 0.00% 0.00% 0.00% 0.00% - - 0.408645 1.341004 0.527611 1.060968 -0.315440 1.212672 1.786594 0.284467 0.5961 0.6096 0.3996 nan nan
2459989 digital_ok 0.00% 0.00% 0.00% 0.00% - - 0.591025 1.422261 0.470569 1.251383 -0.212959 0.510395 1.140067 0.104494 0.5919 0.6107 0.4034 nan nan
2459988 digital_ok 0.00% 0.00% 0.00% 0.00% - - 0.810820 1.865427 0.489981 1.036190 -0.430009 0.258694 1.667037 0.279942 0.5925 0.6106 0.3929 nan nan
2459987 digital_ok 0.00% 0.00% 0.00% 0.00% - - 0.216600 1.333061 0.579834 1.181248 -0.262557 0.862222 -0.407270 0.008938 0.5992 0.6151 0.3927 nan nan
2459986 digital_ok 0.00% 0.00% 0.00% 0.00% - - 0.758332 2.014802 0.671241 1.148958 -0.252321 0.373118 0.399226 0.598283 0.6257 0.6445 0.3419 nan nan
2459985 digital_ok 100.00% 0.00% 0.00% 0.00% - - 1.061618 1.893530 0.674708 0.144025 -0.422742 0.278028 1.043160 13.911452 0.6004 0.6087 0.3967 nan nan
2459984 digital_ok 0.00% 0.00% 0.00% 0.00% - - 0.216354 1.229729 0.684656 0.271609 0.247861 1.913884 0.534503 0.690749 0.6121 0.6279 0.3826 nan nan
2459983 digital_ok 0.00% 0.00% 0.00% 0.00% - - 0.380419 1.306501 0.628145 1.116077 -0.534215 1.134123 0.157339 0.838932 0.6215 0.6483 0.3410 nan nan
2459982 digital_ok 0.00% 0.00% 0.00% 0.00% - - 1.330709 1.457389 0.663184 1.160516 -0.256404 0.806965 0.679295 1.460410 0.6866 0.6951 0.2955 nan nan
2459981 digital_ok 0.00% 0.00% 0.00% 0.00% - - 0.525741 1.137041 0.473687 1.094634 -0.540704 0.745187 1.232211 -0.286959 0.6004 0.6172 0.3973 nan nan
2459980 digital_ok 0.00% 0.00% 0.00% 0.00% - - 0.325505 0.825248 0.370164 1.035114 -0.496101 0.566603 0.819426 1.589329 0.6472 0.6617 0.3158 nan nan
2459979 digital_ok 0.00% 0.00% 0.00% 0.00% - - 0.431720 1.040773 0.173485 0.981616 -0.328303 0.707848 1.664765 0.389584 0.5925 0.6129 0.4004 nan nan
2459978 digital_ok 0.00% 0.00% 0.00% 0.00% - - 0.357882 1.046474 0.266609 1.030602 -0.197413 0.470638 0.351272 -0.166039 0.5935 0.6127 0.4062 nan nan
2459977 digital_ok 0.00% 0.00% 0.00% 0.00% - - 0.457886 1.200289 0.347748 1.013566 0.209822 1.529780 0.138909 -0.420092 0.5540 0.5717 0.3673 nan nan
2459976 digital_ok 0.00% 0.00% 0.00% 0.00% - - 0.356569 1.099980 0.382523 1.062459 0.176996 0.638783 0.934922 0.220405 0.6005 0.6184 0.3919 nan nan

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

In [11]:
htmls_to_display = []
for am_html in auto_metric_htmls:
    html_to_display = ''
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line:
            htmls_to_display.append(html_to_display)
            break

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.

In [12]:
for i, html_to_display in enumerate(htmls_to_display):
    if i == 100:
        break
    display(HTML(html_to_display))

Antenna 65: 2460015

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
65 N03 digital_ok ee Shape 26.059449 24.690559 26.059449 14.128389 14.135122 7.044868 5.900273 7.153203 5.863791

Antenna 65: 2460014

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
65 N03 digital_ok ee Shape 24.593088 24.593088 21.670589 10.887531 10.805839 9.014692 10.569293 4.372422 5.625308

Antenna 65: 2460013

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
65 N03 digital_ok ee Shape 26.074163 26.074163 24.898225 14.245945 14.136088 6.117275 7.190007 6.894251 8.651129

Antenna 65: 2460012

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
65 N03 digital_ok ee Shape 24.667275 24.667275 23.563509 13.984136 13.894777 6.576353 7.801293 7.681827 9.770243

Antenna 65: 2460011

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
65 N03 digital_ok ee Shape 26.543196 26.543196 24.725632 18.658014 18.613437 13.740578 16.210966 6.037885 7.499853

Antenna 65: 2460010

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
65 N03 digital_ok ee Shape 28.705253 28.705253 27.072601 15.052712 15.379989 9.265841 10.470842 5.662304 7.158898

Antenna 65: 2460009

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
65 N03 digital_ok ee Shape 27.384916 27.384916 25.660041 16.658361 16.868447 7.435949 8.905910 5.243936 7.105534

Antenna 65: 2460008

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
65 N03 digital_ok ee Shape 31.661936 30.211714 31.661936 18.579914 18.280907 7.806454 6.695802 6.744117 5.487439

Antenna 65: 2460007

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
65 N03 digital_ok ee Shape 23.637347 23.637347 22.587889 14.271669 14.513646 6.012330 7.262833 5.908707 7.513667

Antenna 65: 2459999

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
65 N03 digital_ok nn Shape nan nan nan nan nan nan nan nan nan

Antenna 65: 2459998

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
65 N03 digital_ok ee Shape 21.093794 21.093794 19.987338 12.268315 12.368718 8.156339 10.400137 4.689562 6.376948

Antenna 65: 2459997

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
65 N03 digital_ok ee Shape 23.267372 23.267372 22.017959 13.019299 13.266608 7.824141 9.683493 8.295054 10.287782

Antenna 65: 2459996

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
65 N03 digital_ok ee Shape 25.573229 25.573229 23.819132 16.151280 16.153198 7.408880 9.306543 3.396996 4.547491

Antenna 65: 2459995

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
65 N03 digital_ok ee Temporal Discontinuties 3.848835 0.512253 1.558083 0.894202 1.249383 -0.368593 1.223226 3.848835 2.134812

Antenna 65: 2459994

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
65 N03 digital_ok nn Shape 1.607135 0.682575 1.607135 0.683002 1.307043 -0.235262 0.865021 -0.378571 -0.456227

Antenna 65: 2459993

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
65 N03 digital_ok ee Temporal Discontinuties 2.058626 0.135874 1.115308 0.425464 1.129750 -0.422386 0.374328 2.058626 0.465625

Antenna 65: 2459991

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
65 N03 digital_ok nn Shape 1.769952 0.571673 1.769952 0.562291 1.185523 -0.413544 0.614940 0.402824 -0.001076

Antenna 65: 2459990

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
65 N03 digital_ok ee Temporal Discontinuties 1.786594 1.341004 0.408645 1.060968 0.527611 1.212672 -0.315440 0.284467 1.786594

Antenna 65: 2459989

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
65 N03 digital_ok nn Shape 1.422261 1.422261 0.591025 1.251383 0.470569 0.510395 -0.212959 0.104494 1.140067

Antenna 65: 2459988

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
65 N03 digital_ok nn Shape 1.865427 1.865427 0.810820 1.036190 0.489981 0.258694 -0.430009 0.279942 1.667037

Antenna 65: 2459987

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
65 N03 digital_ok nn Shape 1.333061 0.216600 1.333061 0.579834 1.181248 -0.262557 0.862222 -0.407270 0.008938

Antenna 65: 2459986

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
65 N03 digital_ok nn Shape 2.014802 2.014802 0.758332 1.148958 0.671241 0.373118 -0.252321 0.598283 0.399226

Antenna 65: 2459985

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
65 N03 digital_ok nn Temporal Discontinuties 13.911452 1.893530 1.061618 0.144025 0.674708 0.278028 -0.422742 13.911452 1.043160

Antenna 65: 2459984

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
65 N03 digital_ok nn Temporal Variability 1.913884 0.216354 1.229729 0.684656 0.271609 0.247861 1.913884 0.534503 0.690749

Antenna 65: 2459983

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
65 N03 digital_ok nn Shape 1.306501 0.380419 1.306501 0.628145 1.116077 -0.534215 1.134123 0.157339 0.838932

Antenna 65: 2459982

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
65 N03 digital_ok nn Temporal Discontinuties 1.460410 1.330709 1.457389 0.663184 1.160516 -0.256404 0.806965 0.679295 1.460410

Antenna 65: 2459981

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
65 N03 digital_ok ee Temporal Discontinuties 1.232211 1.137041 0.525741 1.094634 0.473687 0.745187 -0.540704 -0.286959 1.232211

Antenna 65: 2459980

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
65 N03 digital_ok nn Temporal Discontinuties 1.589329 0.825248 0.325505 1.035114 0.370164 0.566603 -0.496101 1.589329 0.819426

Antenna 65: 2459979

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
65 N03 digital_ok ee Temporal Discontinuties 1.664765 0.431720 1.040773 0.173485 0.981616 -0.328303 0.707848 1.664765 0.389584

Antenna 65: 2459978

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
65 N03 digital_ok nn Shape 1.046474 1.046474 0.357882 1.030602 0.266609 0.470638 -0.197413 -0.166039 0.351272

Antenna 65: 2459977

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
65 N03 digital_ok nn Temporal Variability 1.529780 0.457886 1.200289 0.347748 1.013566 0.209822 1.529780 0.138909 -0.420092

Antenna 65: 2459976

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
65 N03 digital_ok nn Shape 1.099980 1.099980 0.356569 1.062459 0.382523 0.638783 0.176996 0.220405 0.934922
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